TY - JOUR
T1 - On the feasibility of distributed process mining in healthcare
AU - Gatta, R.
AU - Vallati, M.
AU - Lenkowicz, J.
AU - Masciocchi, C.
AU - Cellini, Francesco
AU - Boldrini, Luca
AU - Llatas, C. F.
AU - Valentini, V.
AU - Damiani, A.
PY - 2019
Y1 - 2019
N2 - Process mining is gaining significant importance in the healthcare domain, where the quality of services depends on the suitable and efficient execution of processes. A pivotal challenge for the application of process mining in the healthcare domain comes from the growing importance of multi-centric studies, where privacy-preserving techniques are strongly needed. In this paper, building on top of the well-known Alpha algorithm, we introduce a distributed process mining approach, that allows to overcome problems related to privacy and data being spread around. The introduced technique allows to perform process mining without sharing any patients-related information, thus ensuring privacy and maximizing the possibility of cooperation among hospitals.
AB - Process mining is gaining significant importance in the healthcare domain, where the quality of services depends on the suitable and efficient execution of processes. A pivotal challenge for the application of process mining in the healthcare domain comes from the growing importance of multi-centric studies, where privacy-preserving techniques are strongly needed. In this paper, building on top of the well-known Alpha algorithm, we introduce a distributed process mining approach, that allows to overcome problems related to privacy and data being spread around. The introduced technique allows to perform process mining without sharing any patients-related information, thus ensuring privacy and maximizing the possibility of cooperation among hospitals.
KW - Distributed learning
KW - Healthcare
KW - Process mining
KW - Distributed learning
KW - Healthcare
KW - Process mining
UR - https://publicatt.unicatt.it/handle/10807/203504
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85068473470&origin=inward
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85068473470&origin=inward
U2 - 10.1007/978-3-030-22750-0_36
DO - 10.1007/978-3-030-22750-0_36
M3 - Conference article
SN - 0302-9743
VL - 11540
SP - 445
EP - 452
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
IS - N/A
ER -